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Brain and Cognition xxx (2011) xxx–xxx

Contents lists available at ScienceDirect

Brain and Cognition

journal homepage: www.elsevier.com/locate/b&c

Emotions induced by operatic music: Psychophysiological effects of music, plot,

and acting

A scientist’s tribute to Maria Callas

Felicia Rodica Baltesß, Julia Avram, Mircea Miclea, Andrei C. Miu ⇑

Emotion and Cognition Neuroscience Laboratory, Department of Psychology, Babes-Bolyai University, Cluj-Napoca, CJ 400015, Romania

article

info

abstract

Article history:

Accepted 31 January 2011

Available online xxxx

Keywords:

Operatic music

Music-induced emotions

Physiological differentiation of emotions

Operatic music involves both singing and acting (as well as rich audiovisual background arising from the

orchestra and elaborate scenery and costumes) that multiply the mechanisms by which emotions are

induced in listeners. The present study investigated the effects of music, plot, and acting performance

on emotions induced by opera. There were three experimental conditions: (1) participants listened to

a musically complex and dramatically coherent excerpt from Tosca; (2) they read a summary of the plot

and listened to the same musical excerpt again; and (3) they re-listened to music while they watched the

subtitled film of this acting performance. In addition, a control condition was included, in which an independent

sample of participants succesively listened three times to the same musical excerpt. We measured

subjective changes using both dimensional, and specific music-induced emotion questionnaires.

Cardiovascular, electrodermal, and respiratory responses were also recorded, and the participants kept

track of their musical chills. Music listening alone elicited positive emotion and autonomic arousal, seen

in faster heart rate, but slower respiration rate and reduced skin conductance. Knowing the (sad) plot

while listening to the music a second time reduced positive emotions (peacefulness, joyful activation),

and increased negative ones (sadness), while high autonomic arousal was maintained. Watching the acting

performance increased emotional arousal and changed its valence again (from less positive/sad to

transcendent), in the context of continued high autonomic arousal. The repeated exposure to music

did not by itself induce this pattern of modifications. These results indicate that the multiple musical

and dramatic means involved in operatic performance specifically contribute to the genesis of musicinduced

emotions and their physiological correlates.

Ó 2011 Elsevier Inc. All rights reserved.

‘‘Maria Callas exploded the concept of what beautiful singing

means: Is it pretty sounds and pure tones? Or should beauty

evolve from text, musical shape, dramatic intent and, especially,

emotional truth?’’

(Anthony Tommassini in ‘‘A Voice and a Legend That Still Fascinate;

Callas Is What Opera Should Be’’, The New York Times, September

15, 1997)

Abbreviations: DBP, diastolic blood pressure; ECG, electrocardiogram; GEMS,

Geneva Emotional Music Scale; HF-HRV, power in the high frequency band of HRV;

HR, heart rate; HRV, heart rate variability; IBI, cardiac interbeat intervals; LF-HRV,

power in the low frequency band of HRV; NA, negative affect; PA, positive affect;

PANAS, Positive and Negative Affect Schedule; RR, respiratory rate; RSA, respiratory

sinus arrhythmia; SAM, Self-Assessment Manikin; SBP, systolic blood pressure; SCL,

skin conductance level; SEM, standard error of the mean; VLF-HRV, power in the

very low frequency band of HRV.

⇑ Corresponding author. Address: 37 Republicii, Cluj-Napoca, CJ 400015,

Romania. Fax: +40 264 590967.

E-mail address: andreimiu@gmail.com (A.C. Miu).

1. Introduction

We are often emotionally moved by musical performances.

However, emotions induced by music have only recently drawn

the attention of scholars in cognitive and affective sciences (Juslin

& Vastfjall, 2008; Scherer & Zentner, 2001). Field studies have

confirmed that music pervades everyday life and some of its most

important functions are related to mood change and emotion regulation

(DeNora, 1999; Juslin, Liljestrom, Vastfjall, Barradas, &

Silva, 2008; Sloboda & O’Neil, 2001). In daily life, music generally

increases positive affect, alertness, and focus in the present

(Sloboda, O’Neil, & Ivaldi, 2001). In addition, it provides opportunities

for venting strong emotions, increasing their intensity, or

calming down (DeNora, 1999). Therefore, music has been related

to the genesis and control of emotions.

Despite previous debates on whether music induces emotions in

listeners (i.e., the so-called ‘‘emotivist’’ position), or only expresses

emotions that listeners can recognize (i.e., the ‘‘cognitivist’’

0278-2626/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved.

doi:10.1016/j.bandc.2011.01.012

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


2 F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx

position) (Kivy, 1990; Scherer & Zentner, 2001), the recent literature

has generally supported the former view that music induces

subjective (e.g., self-reported sadness), behavioral (e.g., crying),

and physiological changes (e.g., heart rate [HR – see list of acronyms]

deceleration) that are characteristic of emotions (Bharucha,

Curtis, & Paroo, 2006; Juslin & Vastfjall, 2008; Koelsch, 2005;

Scherer & Zentner, 2001). In addition, the mechanisms by which

music induces emotions (e.g., semantic associations, emotional

contagion based on observation of facial and vocal expressions;

see Bezdek & Gerrig, 2008; Hietanen, Surakka, & Linnankoski,

1998; Lundqvist & Dimberg, 1995) may not be specific to music,

but this possibility has only recently started to be investigated

(for reviews, see Juslin & Vastfjall, 2008; Scherer & Zentner,

2001). The present report stems from the emotivist approach,

and will examine the effects of opera on listeners’ physiological responses

and subjective ratings of their own emotions.

One way to investigate these issues has been to identify physiological

responses during music listening (e.g., Krumhansl, 1997;

Nyklícek, Thayer, & Van Doornen, 1997). This approach has extended

the studies on the physiological differentiation of emotions

induced by facial expressions (e.g., Ekman, Levenson, & Friesen,

1983), images (e.g., Codispoti, Bradley, & Lang, 2001), and even natural

sounds (e.g., Bradley & Lang, 2000). Previous studies indicated

that only certain emotions (e.g., fear, disgust) can be distinguished

based on their autonomic signatures (for review see Levenson,

1992), but the effect sizes were small or medium at best (Cacioppo,

Berntsen, Klein, & Poehlmann, 1997). These findings are not surprising

considering the limited emotional saliency of images and

words presented in laboratory settings. Recent psychophysiological

studies have used more complex stimuli such as films, and consequently

induced more robust experiences of emotion and

physiological responses (e.g., Frazier, Strauss, & Steinhauer, 2004;

Kreibig, Wilhelm, Roth, & Gross, 2007).

1.1. Psychophysiology of music-induced emotions

Like films, music has been shown to produce physiological

changes that can distinguish between emotions. In two landmark

studies, Krumhansl (1997), and Nyklícek et al. (1997) measured a

large array of cardiovascular, respiratory, and electrodermal responses

in association with self-report measures of emotions induced

by music. Emotions were differentiated based on certain

physiological responses such as respiratory sinus arrhythmia

(RSA) and cardiac interbeat intervals (IBI) (Nyklícek et al., 1997).

For instance, sadness ratings correlated positively with IBI, systolic

(SBP) and diastolic blood pressure (DBP), and negatively with skin

conductance level (SCL) (Khalfa, Peretz, Blondin, & Manon, 2002;

Krumhansl, 1997). Emotional arousal was best explained by physiological

changes, which accounted for 62.5% of the variance

(Nyklícek et al., 1997). There is only one psychophysiological field

study that measured emotional ratings, electrodermal and respiratory

responses in a sample of spectators (i.e., 27 listeners) during

several live performances of Wagner’s operas given in the festival

theater of Bayreuth in 1987–1988 (Vaitl, Vehrs, & Sternagel,

1993) 1 . In contrast to laboratory studies, these limited field results

suggested that physiological responses differed between opera leitmotivs,

but there was a weak correspondence between physiological

and subjective measures of emotions.

Psychophysiological studies have thus focused on the coherence

between subjective, behavioral, and physiological components of

music-induced emotions. Lundqvist, Carlsson, and Juslin (2009) reported

an association between music-induced happiness and

1 A recent laboratory study on psychophysiological changes induced by opera came

to our attention while this article was under review. See Bernardi et al. (2009).

greater SCL, and supported the emotivist position. In contrast, another

study found that increased emotional arousal occurred without

changes in SCL (Grewe, Nagel, Kopiez, & Altenmuller, 2007a).

The latter pattern of results was interpreted as evidence for the

cognitivist position, although the participants were clearly instructed

to rate the emotional arousal they felt, and not that expressed

by the music. These apparently divergent results might

be explained by methodological differences, considering that one

study used a self-report instrument that measured changes in several

basic emotions (Lundqvist et al., 2009), and the other measured

changes in arousal and valence across emotions (Grewe

et al., 2007a). In addition, there are emotions specifically induced

by music that are not captured by basic emotion measures such

as the one used by Lundqvist et al. (2009).

1.2. Specific music-induced emotions

It has been argued that aesthetic emotions are deeper and more

significant (Sloboda, 1992), nuanced and subtle (Scherer & Zentner,

2001) than other more general emotions. Indeed, the range of music-induced

emotions goes beyond the emotions captured by the

basic emotion models. A recent field study showed that a nine-factor

model best fitted the emotion descriptors that were chosen by

music listeners who attended a classical music festival (Zentner,

Grandjean, & Scherer, 2008). It included emotion categories (e.g.,

wonder, transcendence) that are not part of any current model of

emotion. The Geneva Emotional Music Scale (GEMS) is the first

questionnaire designed to measure music-induced emotions

(Zentner et al., 2008). To our knowledge, no study has investigated

the correlation between physiological responses and music-induced

emotions measured by GEMS.

1.3. Music-induced chills

Music-induced emotions are often accompanied by physical

sensations such as chills (i.e., tremor or tingling sensations passing

through the body as the result of sudden keen emotion or excitement).

Two landmark studies indicated that the great majority of

people were susceptible to chills (Sloboda, 1991), and these bodily

phenomena were associated with music-induced emotions, especially

sadness and melancholy (Panksepp, 1995). Musical events

such as crescendos or a solo instrument (e.g., a soprano’s voice)

emerging from a softer orchestral background induced chills

(Grewe, Nagel, Kopiez, & Altenmuller, 2007b; Panksepp, 1995).

Psychophysiological studies have shown that music-induced chills

correlated with increases in SCL and HR (Grewe et al., 2007b;

Rickard, 2004). The present study aims to integrate the measurement

of chills, music-induced emotions reflected by GEMS, and a

wider range of physiological changes.

1.4. The duration of musical stimuli

One important aspect that differentiates studies of music-induced

emotions is the duration of stimuli. For instance, many studies

used short (i.e., several seconds), monotonic musical stimuli. It

has been suggested that even less than one second of music is sufficient

to prime an emotional meaning (e.g., Bigand, Vieillard,

Madurell, Marozeau, & Dacquet, 2005; Peretz, Blood, Penhune, &

Zatorre, 2001; Watt & Ash, 1998). However, this approach has at

least two limitations. First, it usually involves forced-choice responses

that increase the difficulty of emotional valence processing

(Bigand et al., 2005; Peretz et al., 2001). Second, the correct

categorization of the emotional content of music may only reflect

the emotions that listeners perceive in music. One second may

not be enough time to develop an emotional response. At any rate,

longer durations of musical stimuli increase the magnitude of

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 3

psychophysiological responses in music-induced emotions (Witvliet

& Vrana, 2007). Psychophysiological studies generally used longer

stimuli (i.e., ranging from 6 to 600 s), and it has been argued that

the use of full music pieces has greater external validity when

investigating emotional responses to music (Grewe et al., 2007a;

Nater, Abbruzzese, Krebs, & Ehlert, 2006; Rickard, 2004).

1.5. Multiple sources of emotion in operatic music

The duration of musical stimuli, as well as the integration of

music with congruent visual and verbal cues are important contributors

to emotional responses that people develop to musical

performance (Bezdek & Gerrig, 2008; Scherer & Zentner, 2001).

Operatic music performance involves both singing and acting,

which multiplies the mechanisms by which emotions are induced

in listeners. Opera adds the power of the dramatic plot and the personality

of the performer to the affective message of the musical

score and the emotional expressivity of voice (Scherer, 1995).

The rich audiovisual background arising from the orchestra and

elaborate scenery and costumes are also important. The objective

of the present study was to investigate for the first time the cumulative

contributions of music listening, learning the context of the

events it portrays (i.e., plot), and watching the acting performance

to emotions induced by opera.

These sources may support the genesis of emotion either independently

or in concert. Research on film music supports the latter

possibility. For instance, music presented during the opening scene

of a film influenced the emotional valence of words that participants

used in their continuations of the narratives (Vitouch,

2001). In addition, judgments of characters displaying neutral

emotions were significantly affected by the emotional content of

the music that accompanied the film (Tan, Spackman, & Bezdek,

2007). Lyrics are also important in emotional responses to music.

For instance, the emotional effects of music and lyrics were investigated

by combining musical excerpts with lyrics that conveyed

the same emotion or another emotion (Ali & Peynircioglu, 2006;

Stratton & Zalanowski, 1994). These studies indicated that lyrics

enhanced emotion in sad and angry music. Furthermore, these

emotions readily transferred to images that were arbitrarily associated

with songs (Ali & Peynircioglu, 2006). In addition, visual

cues such as facial expressions are preattentively integrated with

vocal cues and influence the emotional judgment of the latter (de

Gelder, Bocker, Tuomainen, Hensen, & Vroomen, 1999). Therefore,

it seems likely that facial expressions of singers influence the emotional

processing of music. Overall, music, lyrics, and visual cues

seem to significantly contribute to the genesis of music-induced

emotions, and their concerted contribution may explain why operatic

music is so effective in inducing emotions. However, this complex

issue has not been investigated to date.

1.6. Objectives of the present study

We investigated subjective and physiological emotional responses

to operatic music. In order to maximize external validity,

we chose a dramatically coherent and musically complex excerpt

from Tosca by Giacomo Puccini. The soprano Maria Callas and the

baritone Tito Gobbi gave a legendary interpretation of the main

characters in Tosca, and their 1964 live performance at Covent Garden

was fortunately recorded on film. In this performance, both artists

impress by their emotional identification with the characters,

and the way they deliver the mixture of lust and hate, fear, emotional

vulnerability and indignation through their voice (Huck,

1984). Studying the psychophysiology of emotion during this performance

offers us an opportunity to catch a scientific glimpse of

the emotional force that artists such as Maria Callas have inspired.

The present study had three experimental conditions that

investigated the contributions of music, plot, and acting performance

to emotional responses. First, participants listened to the

musical excerpt. Then, they read a summary of the plot and listened

to the same musical excerpt again. In the third condition,

they re-listened to music while they watched the subtitled film

of this acting performance. In between conditions, we measured

music-induced emotions using both dimensional, and specific music-induced

emotion questionnaires. During the experimental conditions,

cardiovascular, electrodermal and respiratory responses

were continuously recorded, and the participants kept track of

their musical chills.

Since there are very few psychophysiological studies of emotions

in operatic music (and operatic music is so diverse), the present

study was consequently exploratory. Based on the musical and

dramatic content of this musical excerpt, we expected that it

would induce a pattern of emotions characterized by increased

unpleasant emotions (e.g., sadness) and decreased pleasant emotions

(e.g., joyful activation, peacefulness). In addition, based on

the literature in related areas (e.g., sadness induced by films), we

expected a change in the sympathovagal balance, with vagal withdrawal

and sympathetic activation, as well as decreases of SCL and

respiratory rate (RR). We were specifically interested in the way

each successive layer of complexity influenced music-induced

emotions and their physiological correlates.

2. Methods

2.1. Participants

N = 37 healthy, right-handed Romanian volunteers (25 women;

mean age = 21.4 years, ranging between 19 and 24 years), with

good hearing, were selected for this study (out of an initial pool

of 45 volunteers). The sample size was determined by using a priori

statistical power analysis (power = 0.95; alpha = 0.05; effect

size f = 0.25) run in the G-Power 3.1 software (Faul, Erdfelder, Lang,

& Buchner, 2007). The participants had no significant musical education,

but they reported that music was an important part of their

lives. None of the participants reported having listened to Tosca before,

a preference for classic or operatic music, or understood Italian.

These inclusion criteria were important in order to control for

the degree of familiarity with the selected musical piece, and

understanding of the lyrics. None of the participants reported cardiovascular

or neurological problems, or any kind of medical treatment

that would interfere with cardiovascular and autonomic

functions. Participants were asked to refrain from alcohol, caffeine

and smoking at least four hours before the experiment. All the participants

signed an informed consent to participate to the experiment

and the procedures complied with the recommendations of

the Declaration of Helsinki for human studies.

2.2. Materials

We used an excerpt from Giacomo Puccini’s Tosca (Act II), filmed

at Covent Garden in 1964, starring Maria Callas as Floria Tosca, Tito

Gobbi as Scarpia, and Renato Cioni as Mario Cavaradossi (Zeffirelli,

2002). We selected and juxtaposed two excerpts (i.e., excerpt 1 from

11 0 :00 00 [Scarpia: Ed or fra noi parliam da buoni amici]to22 0 :31 00 [Scarpia:

Io? Voi!], and excerpt 2 from 23 0 :36 00 [Tosca: Quanto?]to31 0 :35 00

[Tosca: Perché me ne rimuneri cosi?]) for the following reasons. First,

these excerpts contain the plot (see Supplementary materials)

involving all the three main characters (i.e., Tosca, Scarpia, and Cavaradossi).

Second, these excerpts are musically and dramatically

heterogenous, with a variety of rhythmical dynamics, ascending

and descending scales, large vocal range and emotional tension. In

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


4 F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx

addition, our approach to inducing music-related emotions explicitly

relied on using longer excerpts (e.g., 19 0 :30 00 in the present study)

from popular operatic compositions in order to credibly replicate the

musical context that induces emotions in the real world (Grewe

et al., 2007a; Juslin & Vastfjall, 2008; Rickard, 2004). Music was presented

using Technics RP-F600 high-quality noise canceling closed

headphones. Before the start of the experiment, a test tone was

played, giving participants the opportunity to adjust the loudness

to an individually comfortable level. After the participants read the

plot before the second experimental condition, the experimenters

checked how well the plot was understood by asking the participants

the following questions: (1) who are the main characters; (2)

what happens in this opera; and (3) what happens in this excerpt

of the opera? The great majority of the participants answered correctly

to these questions, but those who omitted or were not sure

of certain details were allowed to read the summary of the plot again

and assisted with supplementary explanations by the experimenters.

This experimental condition started only after each participant

correctly answered all the questions regarding the plot. The video

was displayed on a Samsung SyncMaster 205BW monitor

(50.8 cm), located 1.5 m in front of the participant’s chair. The experimental

room was small and dimly lit, and was maintained at a comfortable

ambient temperature.

2.3. Procedure

There were three conditions of musical experience: (1) music

listening; (2) music re-listening after learning the plot; and (3) music

re-listening while watching the acting performance. Previous

studies revealed that the psychophysiological responses induced

by music are not significantly affected by repeated exposure

(Grewe et al., 2007a, 2007b). However, we also included a control

condition in which an independent sample of N = 9 participants

(five women) successively listened three times to the same musical

excerpt, in order to check whether the repeated exposure to music

influenced the subjective and physiological measures. The same

questionnaires and physiological recordings were used in the main

experiment and the supplementary control condition, except SBP

and DBP that were not measured in the latter condition. The participants

in this control experiment met all the inclusion criteria that

applied to the main experiment.

At the arrival to the laboratory, each participant completed the

general scales of the Positive and Negative Affect Schedule (PANAS-

I) (Watson & Clark, 1994), in order to control for differences in

affective mood before the start of the experiment. After a habituation

period during which participants were explained that several

non-invasive recordings will be taken during music listening, the

physiological electrodes for SCL and electrocardiogram (ECG), as

well as the respiration transducer and an arm cuff coupled to an

automatic blood pressure monitor were attached. Participants

were instructed to sit comfortably and relax, and carefully listen

to the music while monitoring the music-related emotions they

felt without trying to control them in any way. They were instructed

to identify emotions they felt during music listening,

and not emotions that the music expressed. They were also requested

to keep a count on a scratch sheet of the number of chills

they experienced during each condition.

Each condition was preceded by a 5 min interval during which

baseline physiological recordings were made. Participants completed

each condition and unless they wanted a break, they moved

onto the following condition. First, they listened to the musical excerpt.

In the second condition, they were given a summary of the

plot (see Supplementary materials). Using a brief questionnaire,

the experimenters first made sure that participants understood

the plot and knew the characters, and then music was played

again. In the third condition, the participants listened to music

while also watching the acting performance. In order to facilitate

the complete understanding of the plot and acting performance,

the movie was subtitled in Romanian.

After each condition, participants were required to rate the

emotional arousal (1 – non-arousing to 5 – arousing) and valence

(1 – unpleasant to 5 – pleasant) induced by music; and completed

GEMS (Zentner et al., 2008) for music-induced emotions.

2.4. Self-report measures

The positive (PA) and negative affect (NA) scales of PANAS-I

(Watson & Clark, 1994) include 20 items each, which measure

the affective mood in the past few weeks until present. Emotional

arousal and valence were measured using the Self-Assessment

Manikin (SAM) (Bradley & Lang, 1994). SAM is a non-verbal pictorial

assessment technique that directly measures the pleasure and

arousal (as well as dominance, which was not used in the present

study) associated with a person’s affective reaction to a wide variety

of stimuli. For the measurement of emotions induced by music

(e.g., wonder, transcendence, tenderness, peacefulness), we used

the long (i.e., 45 items) variant of GEMS (Zentner et al., 2008).

GEMS scores are grouped on nine factors: wonder; transcendence;

tenderness; nostalgia; peacefulness; power; joyful activation; tension;

and sadness. Whereas the dimensional rating allowed us to

document general changes of emotional arousal and valence, GEMS

offered us the possibility of actually identifying the specific emotions

that were induced by each experimental condition. Self-reports

of chills were also collected.

2.5. Physiological measures

ECG, SCL, and respiration were continuously recorded during

the baseline and experimental conditions, using a BIOPAC MP150

system and specific electrodes and transducers. Blood pressure

was intermittently measured at fixed intervals during the experimental

condition.

2.5.1. Cardiovascular measures

ECG was recorded using disposable pregelled Ag/AgCl electrodes

placed in a modified lead II configuration, at a sample rate of 500

samples/s, and amplified using an ECG100C module. After visual

inspection of the recordings and editing to exclude artifacts in

AcqKnowledge 3.9.0.17, all the recordings were analyzed using Nevrokard

7.0.1 (Intellectual Services, Ljubljana, Slovenia). We calculated

HR, and HR variability (HRV) indices in the time and

frequency domains: mean IBI between successive R waves (HR and

IBI are negatively correlated); power in the high frequency

(HF-HRV) band (0.15–0.4 Hz in adults) of HRV, also known as

RSA; power in the low (LF-HRV) (0.05–0.15 Hz), and very low

frequency (VLF-HRV) (0–0.05 Hz) bands of HRV, as well as LF/HF

ratios. The latter three measures, obtained by spectral analysis, are

reported in normalized units (see Task Force Report, 1996). RSA

reflects vagal modulation of the heart, whereas LF-HRV reflects a

complex interplay between sympathetic and vagal influences (see

Eckberg, 1997; Kingwell et al., 1994; Miu, Heilman, & Miclea,

2009; Task Force of the European Society of Cardiology and Electrophysiology,

1996). These measures were derived from each baseline

and experimental conditions. The statistical analyses of RSA included

respiration frequency as covariate in order to control for

the influence of respiration on this measure. Therefore, the results

reported here controlled for the influence of respiration on RSA.

2.5.2. Skin conductance

After cleaning and abrading the skin of the palms, TSD203

electrodermal response electrodes filled with isotonic gel were attached

to the volar surfaces of the index and medius fingers. SCL

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 5

recordings were amplified using a GSR100C module. We estimated

SCL by extracting the area under the curve (lS/s) from each baseline

and experimental condition, after the downdrift in the SCL

waves was eliminated using the ‘‘difference’’ function of Acq-

Knowledge, as described in (Bechara, Damasio, Damasio, & Lee,

1999; Miu, Heilman, & Houser, 2008).

2.5.3. Respiration

One channel of respiration was measured using a top respiration

band placed on the chest, below the breast. The data were recorded

with the RSP100C module and the TSD201 Transducer of

the Biopac system. TSD201 can arbitrarily measure slow to very

fast thoracic and abdominal respiration patterns with no loss in

signal amplitude, optimal linearity and minimal hystheresis. RR

(in cycles per minute) was calculated breath by breath using Acq-

Knowledge software.

2.5.4. Blood pressure

SBP and DBP (in millimeters of mercury) were measured intermittently

with an automatic blood pressure monitor (Digital Blood

Pressure monitor, Vital System) through an arm cuff at the participant’s

right upper arm. Inflation was initiated at the end of the

baseline, at minutes 5, 10, 15, and at the end of the musical

condition.

2.6. Data reduction

For the continous physiological measurements (i.e., all except

SBP and DBP), we calculated difference scores by subtracting each

baseline measure (i.e., the quiet sitting period immediately preceding

each musical experience condition) from the corresponding

experimental condition measure (see Kreibig et al., 2007). In the

case of SBP and DBP that were intermittently measured, we first

calculated the arithmetic mean of the physiological data from

baseline and experimental conditions, and then derived the same

difference score. The raw scores were transformed to T scores for

normalization.

2.7. Statistical analysis

Data were inspected for outliers (Stevens, 2002, pp. 14–17) –

only 0.8% of the data were excluded. We used repeated measure

ANOVA and ANCOVA, followed by post hoc tests, in order to determine

whether there were differences in emotion experience and

physiological responses between the musical experience conditions.

Effect sizes for t-tests and AN/COVA are reported as Cohen’s

d and g 2 p , and interpreted as follows: d = 0.2 or g2 p

= 0.01 – small effect

size; d = 0.5 or g 2 p

= 0.059 – medium effect size; and d = 0.8 or

g 2 p

= 0.138 – large effect size (Cohen, 1988). We also used the Friedmann

non-parametric test to analyze potential differences between

the frequency of chills in the experimental conditions. In

addition, correlation analyses allowed us to test the association between

emotion experience, physiological responses, and chills.

Simple regressions were used to test whether affective mood

(i.e., PA and NA) predicted affect (i.e., dimensional and specific

emotion ratings) and physiological responses. The data are reported

in the graphs as means ± one standard error of the means

(SEM).

3. Results

3.1. General affect

A 3 (musical experience: music listening vs. learning the plot vs.

watching the acting performance) 2 (sex: women vs. men)

Fig. 1. Changes in emotional arousal and valence (SAM) induced by music listening

(1), learning the plot (2), and watching the acting performance (3).

ANCOVA indicated that musical experience had a significant main

effect on self-reported emotional arousal (F[4, 32] = 6.19, p = 0.002,

g 2 p

= 0.12). NA and PA were included as covariates in these analyses

in order to control for the affective mood of participants before the

experiments.

The analyses of the data from the supplementary control sample

indicated that the repeated exposure to music had no significant

effects on emotional arousal and valence (p= 0.3 for both)

(see Supplementary Fig. 1). In addition, we compared the first music

listening condition in the control experiment to the music listening

condition from the main experiment, in order to verify

their similarity. Indeed, there were no significant differences between

the arousal (t[45] = 1.29, ns) and valence scores

(t[45] = 1.23, ns) in the first conditions of the main and control

experiments, respectively.

Although emotional arousal and valence were not measured before

the first condition because it would have been hard to find an

equally complex, but emotionally neutral stimulus to which to

compare the first experimental condition, we explored the affective

experience that music listening induced by one sample Student t-

tests. The expected mean was the mid-value of the SAM rating

scale. These analyses indicated that music listening was associated

with increased emotional arousal (t[35] = 2.42, p = 0.02, Cohen’s

d= 0.3) and valence scores (t[35] = 8.57, p < 0.0001, Cohen’s d=

1). Next, by comparing between the three experimental condition,

we found that watching the acting performance significantly increased

emotional arousal compared to learning the plot, and music

listening (see Fig. 1). Neither the main effect of sex, nor the interaction

of sex musical experience on emotional arousal and valence

were statistically significant.

3.2. Music-induced emotions

The effects of musical experience and sex on music-induced

emotions measured by GEMS were also investigated. A 3 (musical

experience: music listening vs. learning the plot vs. watching the

acting performance) 2 (sex: women vs. men) ANCOVA indicated

that musical experience induced specific emotions. NA and PA

were again included as covariates in these analyses.

The analyses of the data from the supplementary control sample

indicated that the repeated exposure to music had no significant

effects on any of the GEMS measures (p > 0.1 for all) (see

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


6 F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx

decreased IBI (F[4, 32] = 2.98, p = 0.05, g 2 p

= 0.08), and SCL

(F[4, 32] = 3.2, p = 0.04, g 2 p

= 0.09) in comparison to music listening.

3.4. Experienced chills

The repeated exposure of the independent control sample to

music had no significant effect on self-reported chills (p = 0.3).

There were no differences between the frequency of chills in the

control and main experiments, respectively.

A Friedman non-parametric test compared between the three

experimental conditions in the main experiment and indicated

that the exposure to the acting performance significantly increased

the number of reported chills (v 2 = 8.92, p = 0.01) in comparison to

learning the plot and music listening.

3.5. Relationships between music-induced affect, chills, and

physiological responses

Fig. 2. Changes in GEMS scores induced by music listening (1), learning the plot (2),

and watching the acting performance (3).

Supplementary Fig. 2). We also compared the pattern of GEMS

scores between the first conditions of the main and control experiments.

There was only one significant difference on tenderness

(t[45] = 2.25, p = 0.02), with higher scores in the music listening

condition of the main experiment.

By comparing between the three experimental condition, we

found that learning the plot and watching the acting performance

had significant effects on distinct music-induced emotions (see

Fig. 2). On the one hand, learning the plot reduced the scores of

peacefulness (F[4, 32] = 7.84, p = 0.0009, g 2 p

= 0.23) and joyful activation

(F[4, 32] = 5.85, p = 0.004, g 2 p

= 0.17), and increased sadness

(F[4, 32] = 10.98, p = 0.0001, g 2 p

= 0.32). On the other hand, watching

the acting performance increased the scores of wonder

(F[4, 32] = 8.13, p = 0.0007, g 2 p

= 0.23) and transcendence

(F[4, 32] = 4.02, p = 0.02, g 2 p

= 0.11). Neither the main effect of sex,

nor the interaction of sex musical experience on specific emotions

were statistically significant.

3.3. Physiological responses

The analyses of the data from the supplementary control sample

indicated that the repeated exposure to music had no significant

effects on any of the physiological measures (p > 0.39 for all)

(see Supplementary Fig. 3). However, a couple of physiological

measures were significantly different between the first conditions

of the main and control experiments: IBI (t[45] = 4.77, p < 0.0001)

and RR (t[45] = 2.09, p = 0.04), with lower values in the first condition

of the control experiment.

There were significant main effects of musical experience on

physiological responses. In comparison to baseline measures, music

listening (i.e., the first condition) significantly decreased RR

(F[4, 32] = 9.12, p = 0.005, g 2 p

= 0.29), IBI (F[4, 32] = 3.11, p = 0.02,

g 2 p = 0.09), and SCL (F[4, 32] = 29.76, p < 0.0001, g2 p

= 0.75). In the

following experimental conditions, both learning the plot, and

watching the acting performance specifically influenced physiological

measures (Fig. 3). On the one hand, learning the plot significantly

decreased RSA (F[4, 32] = 3.05, p = 0.05, g 2 p

= 0.08) and

increased LF-HRV (F[4, 32] = 3.49, p = 0.03, g 2 p

= 0.09) and LF/HF

(F[4, 32] = 3.77, p = 0.02, g 2 p

= 0.1) in comparison to music listening.

On the other hand, watching the acting performance significantly

We analyzed the correlations between emotions, chills, and

physiological responses within each musical experience condition.

The following paragraph reports the main patterns of correlations

for which we had a priori hypotheses (for detailed results, see

Tables 1–3). These analyses indicated that LF-HRV positively, and

RSA negatively correlated with emotional arousal after learning

the plot. In the same condition, the frequency of chills also correlated

with arousal. In contrast, RR positively correlated with emotional

valence (i.e., increased RR for positive valence) during music

listening.

The analyses of music-induced emotions showed that LF-HRV

positively, and RSA negatively correlated with the level of wonder,

power, and joyful activation after learning the plot. Also, LF-HRV

positively and RSA negatively correlated with the frequency of

chills both after learning the plot, and while watching the acting

performance. Chills consistently correlated positively with the levels

of wonder and transcendence in all three musical experience

conditions. We also checked if this correlation was replicated in

the control experiment and we confirmed that chills correlated significantly

with wonder (r = 0.65, p = 0.05) and marginally with

transcendence (r = 0.6, p = 0.08). Another consistent pattern of positive

correlations was that between RR, wonder (during all three

musical experience conditions), and transcendence (during music

listening, and watching the acting performance).

3.6. Previous mood and music-induced affect

PA and NA significantly correlated (r = 0.45, p < 0.01), but the

low correlation allowed us to use both as predictors (i.e., negligible

multicollinearity). Our hypotheses were that NA would positively

predict unpleasant emotions measured by GEMS (i.e., nostalgia,

sadness, tension), and negatively predict pleasant emotions (i.e.,

wonder, transcendence, power, tenderness, peacefulness, joyful

activation). We also expected that PA would negatively predict

unpleasant emotions and positively predict pleasant emotions. In

addition, based on the work of Panksepp (1995), we also hypothesized

that NA would negatively predict chills and RSA. On the

assumption that only the first condition (i.e., music listening)

would be directly affected by previous mood, regression analyses

were run on music-induced emotions and chills recorded during

the first condition. The results indicated that power (R = 0.53,

p = 0.0009, g 2 p

= 0.28) and joyful activation (R = 0.45, p = 0.05,

g 2 p

= 0.21) were negatively predicted by NA. In contrast, PA positively

predicted power (R = 0.51, p < 0.001, g 2 p

= 0.26) and joyful

activation (R = 0.38, p = 0.02, g 2 p = 0.15).

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 7

Fig. 3. Changes in interbeat intervals (IBI), heart rate (HR), power in the very low frequency (VLF), and low frequency (LF) bands of heart rate variability, respiratory sinus

arrhythmia (RSA), sympathovagal balance (LF/HF), skin conductance level (SCL), systolic blood pressure (SBP), diastolic blood pressure (DBP), and respiratory rate (RR)

induced by music listening (1), learning the plot (2), and watching the acting performance (3).

4. Discussion

The results of this study confirmed that music listening, learning

the plot, and watching the acting performance had specific effects

on emotional responses measured at the subjective and

physiological levels.

4.1. Effects of music, plot and acting

In comparison to expected mean scores, music listening increased,

as one would expect, emotional arousal and valence. In

addition, music listening decreased RR, IBI and SCL, in comparison

to baseline physiology. These results seem to extend previous

observations that sad music is associated with decreased SCL,

and sadness induced by music is well discriminated by respiratory

changes (Krumhansl, 1997; Nyklícek et al., 1997). Moreover, our

observation of decreased SCL associated with this music excerpt

is also in line with studies that induced sadness by directed facial

action tasks (Ekman et al., 1983; Levenson, 1992).

It may seem that the pattern of reduced RR and SCL, and increased

HR (i.e., decreased IBI) in the music listening condition is

contradictory. Early observations indicated that the minor tonalities

of music increased HR (Hyde & Scalapino, 1918), whereas

the tempo of music influenced RR (Diserens, 1920). Bernardi and

colleagues (2009) have recently reported that music crescendos

or emphases (e.g., in Nessun dorma from Puccini’s Turandot) induced

skin vasoconstriction along with increases in blood pressures

and HR. There was also increased breath depth during

music crescendos, but these modulations of respiratory power

were independent of cardiovascular modulations. The present

study also shows that music listening independently modulated

RR and HR, and the former correlated with negative valence, wonder

and transcendence. Also in line with the present results, Nakahara,

Furuya, Francis, & Kinoshita, (2010) found that playing Bach’s

No. 1 Prelude with emotional expression increased HR and decreased

RR in pianists, in comparison to playing the same piece

without emotional expression. Therefore, these studies suggest

that music-induced emotions can independently modulate cardiovascular

and respiratory activities, and this pattern of physiological

changes may contribute to the receptiveness or arousal to music

(Bernardi et al., 2009; the present study) and the capacity of

performers to incorporate expressiveness in their performance

(Nakahara, Furuya, Francis, & Kinoshita, 2010).

Our control analyses on the data from an independent sample

indicated that re-listening to the musical excerpt for three times

did not increase emotional arousal and valence, or induced additional

physiological changes by itself. Whereas there were no differences

between the conditions of the control experiment,

which argued that repeated music listening alone did not affected

the subjective and physiological measurements, the relevance of

the physiological measurements from the control experiment is

limited. There were differences in IBI and RR between the sample

used in the main and control experiments, respectively. This was

probably due to the reduced sample size in the control experiment

(N = 9, in comparison to N = 37 in the main experiment). Overall,

the control data supported the view that the changes observed in

the main experiment were not due to repeated music listening

alone, although this inference should be taken with caution in regard

to some of the physiological results. Replicating the control

findings with a sample size that is similar to that of the main

experiment would be necessary in order to unequivocally confirm

that the repeated music listening alone does not change physiological

activity.

Learning the plot before listening to the musical excerpt the

second time (in the main experiment) induced a pattern of emotional

changes that included reduced peacefulness, joyful activation,

and increased sadness. At the physiological level, learning

the plot decreased RSA and increased LF-HRV. The change in RSA

reflects vagal suppression that has been associated with negative

emotional states and traits, such as anxiety and depression (Bleil,

Gianaros, Jennings, Flory, & Manuck, 2008; Miu et al., 2009). The

summary of the plot that the participants read before they

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


8 F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx

Table 1

Correlations between physiological responses, chills, and affect during music listening.

Geneva Emotional Music Scale Chills

Self-Assessment

Manikin

Sadness Tension

Arousal Valence Wonder Transcendence Power Tenderness Nostalgia Peacefulness Joyful

activation

Systolic blood pressure (SBP) 0.23 0.12 0.23 0.36 * 0.34 * 0.13 0.29 0.03 0.17 0.3 0.07 0.09

Diastolic blood pressure (DBP) 0.06 0.17 0.13 0.16 0.15 0.06 0.02 0.11 0.15 0.15 0.03 0.11

Skin conductance level (SCL) 0.08 0.12 0.05 0.15 0.14 0.12 0.14 0.01 0.02 0.15 0.07 0.11

Respiratory rate (RR) 0.01 0.4 * 0.35 * 0.35 * 0.7 0.23 0.32 0.08 0.12 0.04 0.00 0.27

Cardiac interbeat intervals (IBI) 0.05 0.11 0.17 0.01 0.21 0.01 0.15 0.01 0.02 0.1 0.02 0.21

Heart rate (HR) 0.04 0.08 0.14 0.01 0.18 0.03 0.12 0.02 0.04 0.11 0.06 0.18

Power in the very low frequency of heart rate variability (VLF-HRV) 0.21 0.31 0.07 0.02 0.6 0.36 * 0.11 0.45 ** 0.07 0.1 0.08 0.03

Power in the low frequency of heart rate variability (LF-HRV) 0.1 0.05 0.003 0.09 0.7 0.03 0.29 0.13 0.21 0.11 0.09 0.04

Respiratory sinus arrhythmia (RSA or HF-HRV) 0.02 0.01 0.07 0.05 0.01 0.07 0.27 0.16 0.25 0.13 0.04 0.15

Ratio between low and high frequency powers of heart rate variability 0.15 0.15 0.19 0.07 0.16 0.09 0.22 0.15 0.1 0.00 0.04 0.05

(LF/HF)

Chills 0.22 0.08 0.44 ** 0.46 ** 0.11 0.00 0.19 0.12 0.12 0.1 0.26

p 6 0.05.

p 6 0.01.

*

**

re-listened to the musical excerpt described negative emotional

events (e.g., Scarpia tortures Cavaradossi and harasses Tosca; see

Supplementary materials). Therefore, we argue that the sadness induced

by learning the plot triggered vagal suppression that was

neither explained by concomitant respiratory changes (i.e., RR

was controlled for in the analyses of RSA), nor by re-listening to

the musical excerpt by itself. The increase in LF-HRV suggests that

learning the plot also facilitated sympathetic activity. However, LF

probably reflects a complex interplay between sympathetic and

vagal influences on the heart (Eckberg, 1997; Miu et al., 2009), so

the effect of learning the plot on sympathetic activity should be taken

with caution. Overall, learning the plot significantly influenced

music-induced emotions and changed sympathovagal balance in

the direction of greater preparedness for action.

Watching the acting performance increased emotional arousal

and valence (SAM) compared to the first two experimental conditions.

Furthermore, it increased wonder and transcendence

(GEMS). Notably, wonder and transcendence are emotions that

are specifically induced by music (Zentner et al., 2008). In comparison

to music listening and learning the plot, watching the acting

performance added social-emotional and visuospatial cues to the

musical experience: facial expressions, gestures and postures,

translated lines, and scenery. These factors probably contributed

to the semantic processing of music and vocal expressions, and

we argue that this experimental condition best approximated the

full musical experience of listeners attending a live opera performance.

Watching the acting performance decreased IBI and SCL

in comparison to music listening. Previous studies reported that

music-induced sadness ratings correlated positively with IBI and

negatively with SCL (Krumhansl, 1997; Nyklícek et al., 1997). In

addition, watching the acting performance was also related to significantly

more music-induced chills. Another recent study showed

that music-induced chills correlated with increased SCL and HR

(Guhn, Hamm, & Zentner, 2007). The apparent divergence between

these previous results and the present findings of increased wonder

and transcendence associated with decreased IBI and SCL,

and increased music-induced chills may be explained by differences

in experimental design and measures. First, previous studies

used short excerpts from classical orchestral music, whereas we focused

on opera. Second, the previous studies investigated music

listening alone, whereas our observations are based on a condition

that involved music listening while watching the acting performance.

Third, their conclusions are based on comparisons between

music expressing negative and positive emotions, identified using

basic emotions questionnaires. In the present experiment, watching

the acting performance induced wonder and transcendence

measured using GEMS. Overall, our results show for the first time

that watching the acting performance contributes to music-induced

wonder and transcendence that are associated with decreased

IBI and SCL, and increased chills.

In summary, both music listening (compared to baseline), and

watching the acting performance (compared to music listening)

decreased IBI and SCL. As shown in Fig. 3, IBI followed the same

decreasing trend, whereas SCL remained at the same level after

learning the plot compared to music listening. This means that

learning the plot did not significantly influence these physiological

variables, but they nonetheless remained at the level induced by

music listening (i.e., they did not return to baseline). Therefore,

music listening decreased RR, IBI, and SCL, learning the plot had

no effect on these measures, and watching the acting performance

significantly decreased IBI and SCL again. This indicates that IBI and

SCL are the main physiological variables that are influenced by music

listening and watching the acting performance. The only variables

that were specifically influenced by learning the plot were

RSA and LF-HRV, which indicates that they are sensitive to the

addition of meaning in this context.

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 9

4.2. Coherence between subjective and physiological changes

Table 2

Correlations between physiological responses, chills, and affect during music listening after learning the plot.

Geneva Emotional Music Scale Chills

Self-Assessment

Manikin

Sadness Tension

Arousal Valence Wonder Transcendence Power Tenderness Nostalgia Peacefulness Joyful

activation

Systolic blood pressure (SBP) 0.12 0.1 0.23 0.09 0.24 0.08 0.05 0.01 0.05 0.04 0.01 0.1

Diastolic blood pressure (DBP) 0.02 0.15 0.00 0.16 0.13 0.39 ** 0.23 0.19 0.11 0.00 0.08 0.05

Skin conductance level (SCL) 0.02 0.07 0.13 0.09 0.06 0.04 0.18 0.06 0.08 0.02 0.47 ** 0.18

Respiratory rate (RR) 0.08 0.29 0.33 * 0.42 0.26 0.13 0.1 0.04 0.32 * 0.01 0.01 0.45 **

Cardiac interbeat intervals (IBI) 0.09 0.21 0.27 0.17 0.34 * 0.11 0.16 0.04 0.33 * 0.1 0.18 0.09

Heart rate (HR) 0.05 0.16 0.25 0.13 0.35 * 0.05 0.13 0.02 0.29 0.09 0.22 0.07

Power in the very low frequency of heart rate variability (VLF-HRV) 0.02 0.23 0.08 0.07 0.02 0.07 0.2 0.15 0.16 0.02 0.13 0.13

Power in the low frequency of heart rate variability (LF-HRV) 0.36 * 0.02 0.56 ** 0.56 ** 0.46 ** 0.39 * 0.43 ** 0.01 0.47 ** 0.44 ** 0.29 0.35 *

Respiratory sinus arrhythmia (RSA or HF-HRV) 0.34 * 0.01 0.56 ** 0.56 ** 0.46 ** 0.41 ** 0.43 ** 0.00 0.47 ** 0.42 ** 0.29 0.35 *

0.16 0.15 0.09 0.14 0.17 0.08 0.07 0.03 0.11 0.00 0.07 0.31

Ratio between low and high frequency powers of heart rate variability

(LF/HF)

Chills 0.34 * 0.03 0.36 * 0.39 * 0.28 0.02 0.27 0.1 0.4 * 0.12 0.36 *

p 6 0.05.

p 6 0.01.

*

**

There has been an active emotivist vs. cognitivist debate between

scholars who argue that music listeners really experience

emotions, or only identify emotions that music expresses (Kivy,

1990; Scherer & Zentner, 2001). This study integrated subjective

and physiological measures of emotional responses, thus adding

to the developing literature on the psychophysiology of music. In

this line, a novel and important contribution of the present study

is that we correlated music-induced emotions measured with a domain-specific

instrument (i.e., GEMS), with an extensive array of

emotion-related physiological changes. For instance, we found that

music-induced wonder positively correlated with RR and chills

across conditions. Moreover, by comparing the correlations of subjective

and physiological changes between the three experimental

conditions, one would observe that the psychophysiological coherence

increases the most after learning the plot. This might suggest

that the addition of meaning may be more closely related to the

coherence between subjective and physiological changes induced

by music, than the provision of additional sensory information

(e.g., watching the acting performance).

4.3. Affective mood and sex

The present findings that affective mood predicted emotions induced

by music listening (e.g., power, joyful activation) suggests

that future studies of music-induced emotions should control for

this potential confound. Specifically, NA negatively predicted, and

PA positively predicted power and joyful activation induced by

music listening. This argues for the role of affective mood in the

genesis of music-induced emotions, which is also in line with other

studies (see Kreutz, Ott, Teichmann, Osawa, & Vaitl, 2008). In a recent

field study (F.R. Baltes, M. Miclea, & A.C. Miu, unpublished

observations), we have confirmed and extended the relationship

between the affective mood that the participants reported before

the beginning of a live opera performance, and the music-induced

sadness and transcendence (GEMS). This indicates that the influence

of affective mood is not limited to wonder and transcendence.

However, the specificity of this association in relation to the musical

stimuli, and the physical setting (i.e., laboratory vs. field studies)

might be investigated by future studies.

We also controlled for sex differences in the present analyses. A

previous study showed that in comparison to men, women rated

the chill-producing songs as being sadder (Panksepp, 1995). Another

study reported that women showed elevated SCL to heavy

metal compared to Renaissance music (Nater et al., 2006). In light

of these results, the present study tested the effects of sex, and the

interaction of sex and musical experience. We expected that after

learning the plot, and especially during watching the acting performance,

women would be more reactive due to increased emotional

empathy with the female character in the musical excerpt. However,

we found no significant main effect, or interaction of sex with

musical experience, on subjective or physiological responses.

4.4. Potential limitations and implications

One potential limit is that the mere repeated exposure may

have influenced the present pattern of results. However, this

possibility was controlled by measuring the same subjective and

physiological responses while an independent control sample

re-listened to the same musical excerpt for three times. The results

from this sample indicated that the emotional arousal and valence,

the music-induced emotions, or the physiological measures did not

change with mere re-listening. This is also in line with the studies

of Grewe et al. (2007a, 2007b). However, we acknowledge that a

real limitation of the present study comes from the small size of

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


10 F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx

Table 3

Correlations between physiological responses, chills, and affect during music listening while watching the acting performance.

Geneva Emotional Music Scale Chills

Self-Assessment

Manikin

Sadness Tension

Arousal Valence Wonder Transcendence Power Tenderness Nostalgia Peacefulness Joyful

activation

Systolic blood pressure (SBP) 0.17 0.18 0.15 0.39 * 0.09 0.2 0.21 0.1 0.09 0.22 0.39 ** 0.02

Diastolic blood pressure (DBP) 0.13 0.23 0.25 0.32 0.1 0.12 0.04 0.01 0.13 0.1 0.21 0.017

Skin conductance level (SCL) 0.00 0.16 0.04 0.05 0.09 0.01 0.1 0.05 0.02 0.16 0.1 0.09

Respiratory rate (RR) 0.32 0.2 0.39 ** 0.49 ** 0.34 * 0.2 0.08 0.01 0.27 0.28 0.22 0.53 **

Cardiac interbeat intervals (IBI) 0.17 0.05 0.18 0.25 0.01 0.03 0.01 0.12 0.03 0.21 0.07 0.04

Heart rate (HR) 0.19 0.00 0.17 0.25 0.04 0.06 0.08 0.16 0.00 0.17 0.02 0.00

Power in the very low frequency of heart rate variability (VLF-HRV) 0.02 0.00 0.13 0.04 0.12 0.15 0.12 0.25 0.2 0.00 0.13 0.14

Power in the low frequency of heart rate variability (LF-HRV) 0.08 0.06 0.16 0.1 0.01 0.01 0.11 0.11 0.03 0.00 0.04 0.36 *

Respiratory sinus arrhythmia (RSA or HF-HRV) 0.02 0.12 0.16 0.1 0.03 0.02 0.11 0.06 0.02 0.12 0.05 0.38 *

0.05 0.03 0.16 0.22 0.19 0.08 0.07 0.03 0.15 0.06 0.27 0.29

Ratio between low and high frequency powers of heart rate variability

(LF/HF)

Chills 0.2 0.12 0.36 * 0.34 * 0.27 0.12 0.22 0.12 0.28 0.24 0.023

p 6 0.05.

p 6 0.01.

*

**

the control sample in comparison to the sample from the main

experiment.

In light of the previous literature, musical expertise and (not)

understanding the original language performance are also unlikely

to have confounded our results. For instance, Bigand et al. (2005)

showed that the classification of musical excerpts according to

the emotional content did not differ between music graduates

and nonmusicians. Another study found that emotional responses

are not affected by song translation of non-native original language

performance (Chiaschi, 2007), such as we did in our third experimental

condition. It is also unlikely that listening to music with

eyes open influenced music-induced emotions in the present study

(Kallinen, 2004). However, future studies might control for personality

variables (e.g., absorption) that are known to affect emotional

arousal induced by music (Kreutz et al., 2008).

These results have theoretical and methodological implications.

First, they contribute to the literature supporting the emotivist position

in the psychology of music. Second, they also add evidence in

favor of the physiological differentiation of emotions. Third, considering

that psychophysiological measures tended to correlate

more highly with GEMS scores, and wonder and transcendence

played a particularly prominent role, the present results emphasize

the utility of domain-specific instruments to assess music-induced

emotions. Fourth, many previous studies have paid a high price for

experimental control, by using sound clips lasting a few seconds

and crude measures of emotion (Peretz et al., 2001; Vieillard

et al., 2008). Although these studies contributed to the understanding

of the minimal conditions that are necessary to express an

emotional meaning, it remains often unclear whether findings

from such studies have any bearing on the experience of music

in real life. Consequently, we chose to use a 19 min excerpt from

Tosca, edited to contain a coherent plot, in order to realistically

simulate the real life conditions in which opera induces emotions.

The rich and complex pattern of psychophysiological results in the

present study underscores the importance of external validity in

laboratory studies of music-induced emotions.

Each experimental condition in the present study manipulated

an additional variable in relation to the previous conditions (i.e.,

the plot for the second condition, and the visual context for the

third condition). The rationale behind this type of within-subject

design is that any change that develops in one condition relative

to the previous one is determined by the additional variable that

was manipulated in that condition. However, it is possible that

rather than being specifically induced by each new variable that

was manipulated in a certain experimental condition, the changes

could be due to simply increasing the sensory and semantic complexity

of the musical experience. For instance, the visual context

that was added in the third experimental condition might have

clarified the meaning of the music, or allowed increased depth of

processing in relation to the first two conditions. Other studies

have used similar approaches by juxtaposing music and images,

or lyrics and music, and claimed that emotional changes were specifically

induced by the variable that differed between conditions

(e.g., Ali & Peynircioglu, 2006).

One may wonder whether this pattern of findings might generalize

to all opera, or is unique to this style of operatic music performance

(i.e., pertaining to verismo), composer, composition, excerpt,

or interpretation. Scherer and Zentner (2001) have emphasized

that music-induced emotions depend on several factors, such as

structural features of music (i.e., pitch, melody, tempo, rhythm,

harmony), performance features (e.g., physical appearance, expression,

reputation, technical and interpretative skills of the performer),

listener features (e.g., musical expertise, personality,

affective mood), and contextual features (e.g., location of the

performance, social framing of the event). The present study

investigated the influence of affective mood, and controlled for

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and

Cognition (2011), doi:10.1016/j.bandc.2011.01.012


F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 11

important listener features (i.e., musical expertise, familiarity with

the selected musical piece, preference for classic or operatic music).

In addition, all the participants listened to the music in the

same physical setting (i.e., our laboratory). This argues for the generality

of our findings. It was beyond the purpose of this study to

investigate the influence of musical structure, and performance

features. It is likely that the stellar performance of Maria Callas

and Tito Gobbi in this Tosca performance increased the effectiveness

of this excerpt in inducing emotions. However, we speculate

that the pattern of emotions reported here would not have been

different had we used another interpretation of this opera by artists

that are vocally and dramatically comparable (or at least

close) to Maria Callas and Tito Gobbi. Future studies might investigate

whether these findings can be replicated with excerpts from

other operas.

4.5. Conclusion

In conclusion, this study found that music listening, learning the

plot, and watching the acting performance had specific effects on

music-induced emotions and their physiological correlates. Opera

poses enormous challenges to research due to the multitude of

musical and dramatic means by which it induces emotions.

Although the present study only scratched the surface, it opens

new perspectives for future studies on the mechanisms of musicinduced

emotions in opera.

Acknowledgments

We are grateful to Dr. Laurel J. Trainor and two anonymous

reviewers for important suggestions that helped us in improving

the present article, and Dr. Marcel Zentner for permission to use

the Geneva Emotional Music Scale (GEMS-45) in the study. We also

thank Silviu Matu for help with data collection. This research was

supported by the 2010 Arnold Bentley Award from the Society for

Education, Music, and Psychology (SEMPRE) to R.F.B. and A.C.M.,

and grant 411/2010 from the National University Research Council

to A.C.M.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, in

the online version, at doi:10.1016/j.bandc.2011.01.012.

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